code: def levenshtein(str1, s2):
      """
      Distance between two strings
      """
      N1 = len(str1)
      N2 = len(s2)
  
      stringRange = [range(N1 + 1)] * (N2 + 1)
      for i in range(N2 + 1):
          stringRange[i] = range(i, i + N1 + 1)
      for i in range(0, N2):
          for j in range(0, N1):
              if str1[j] == s2[i]:
                  stringRange[i + 1][j + 1] = min(
                      stringRange[i + 1][j] + 1,
                      stringRange[i][j + 1] + 1,
                      stringRange[i][j],
                  )
              else:
                  stringRange[i + 1][j + 1] = min(
                      stringRange[i + 1][j] + 1,
                      stringRange[i][j + 1] + 1,
                      stringRange[i][j] + 1,
                  )
      return stringRange[N2][N1]
  
file_path: pyAudioAnalysis/pyAudioAnalysis/audioVisualization.py
imports: from __future__ import print_function
  import shutil, struct, simplejson
  from scipy.spatial import distance
  from pylab import *
  import ntpath
  import os
  from pyAudioAnalysis import MidTermFeatures
  from pyAudioAnalysis import audioTrainTest
  import sklearn
  import sklearn.discriminant_analysis
  import sys
  from sklearn.preprocessing import StandardScaler
  import plotly.express
label_desc: Use image node_id 2 for calling a global function with example usage: levenshtein(str1, s2) and returns: stringRange